The Human Touch: Leveraging Human Evaluation for Better AI

As AI systems become more ubiquitous and sophisticated, ensuring their quality and reliability is paramount. While automated metrics provide valuable insights, they often fall short in capturing the nuances of human-like performance, particularly for complex AI components like agents and workflows. This is where human evaluation becomes indispensable.

Why Human Evaluation Matters

Automated tests are fantastic for checking basic functionality, syntax, and some performance metrics. However, they struggle with subjective qualities that are crucial for a truly effective AI experience:

• Understanding Nuance: Can the AI truly understand complex or ambiguous requests?
• Contextual Awareness: Does the AI adapt its response appropriately to different situations?
• Empathy and Tone: Is the AI's communication helpful, polite, and encouraging, especially in sensitive domains?
• Creativity and Open-endedness: For generative AI, is the output truly novel, relevant, and engaging?
• Truthfulness and Factuality: Beyond simple accuracy, does the AI avoid subtle disinformation or misleading statements?

These are areas where human perception, experience, and common sense are irreplaceable. For example, an automated metric might count keywords, but a human can assess if the response genuinely addresses the user's underlying need.

Evals.do: Bridging the Gap with Comprehensive Evaluation

Platforms like Evals.do are designed to facilitate this blend of automated and human evaluation, offering a comprehensive evaluation platform for your AI functions, workflows, and agents.

Let's look at a practical example. Imagine you're evaluating a customer support AI agent. While you can track response time and the number of resolved tickets automatically, how do you assess the quality of the interaction from the customer's perspective?

As seen in the evaluators array, Evals.do explicitly supports human-review. This means you can define subjective metrics like 'helpfulness' and 'tone' where human evaluators provide ratings based on their judgment.

How Evals.do Incorporates Human Feedback

Evals.do works by:

1. Defining Custom Criteria: You set up the specific metrics and scales (like 0-5 for helpfulness) that are important for your AI component.
2. Collecting Data: Your AI components' outputs are captured.
3. Processing with Human Evaluators: This is where the "human touch" comes in. Evals.do can channel these outputs and criteria to human reviewers (either internal teams or external crowd-workers) who then assess and score the AI's performance based on your guidelines.
4. Generating Reports: The human evaluations are integrated with automated metrics to provide a holistic view of your AI's performance, highlighting where it excels and where it needs improvement.

Beyond Customer Support: Applications Across AI

The principle of combining human and automated evaluation extends to various AI applications:

• Generative AI: Humans can assess creativity, coherence, factual accuracy, and safety of generated text, images, or code.
• Code Generation: Evaluators can check functional correctness (can the code be executed?), but also readability, best practices, and elegant solutions.
• Search and Recommendation Systems: Humans can judge the relevance and diversity of search results or recommendations.
• Agentic Workflows: When complex AI agents perform multi-step tasks, human oversight ensures the overall outcome is correct, efficient, and meets the user's intent.

FAQs About AI Evaluation

Q: How does Evals.do work?
A: Evals.do works by allowing you to define custom evaluation criteria, collect data from your AI components, and process it through various evaluators (human, automated, AI) to generate performance reports.

Q: What types of AI components can I evaluate?
A: You can evaluate functions, workflows, and agents, as well as specific AI models or algorithms within your system.

Q: Can I include human feedback in my evaluations?
A: Yes, Evals.do supports integrating both human feedback and automated metrics for comprehensive evaluation.

Conclusion

While AI continues to advance at a rapid pace, the "human touch" remains an irreplaceable element in ensuring the quality, reliability, and ultimate ethical deployment of these systems. By strategically leveraging human evaluation alongside robust automated testing, platforms like Evals.do empower developers and organizations to build AI that truly meets high standards and delivers real-world value. Don't just make your AI smart; make it good.